Restless Legs Syndrome Prevalence and Impact
Bibliographic record
Abstract
BACKGROUND: Restless legs syndrome (RLS), a common sensorimotor disorder, has a wide range of severity from merely annoying to affecting sleep and quality of life severely enough to warrant medical treatment. Previous epidemiological studies, however, have failed to determine the prevalence of those with clinically significant RLS symptoms and to examine the life effects and medical experiences of this group. METHODS: A total of 16 202 adults (aged >/=18 years) were interviewed using validated diagnostic questions to determine the presence, frequency, and severity of RLS symptoms; respondents reporting RLS symptoms were asked about medical diagnoses and the impact of the disorder and completed the Short Form-36 Health Survey (SF-36). Criteria determined by RLS experts for medically significant RLS (frequency at least twice a week, distress at least moderate) defined "RLS sufferers" as a group most likely to warrant medical treatment. RESULTS: In all, 15 391 fully completed questionnaires were obtained; in the past year, RLS symptoms of any frequency were reported by 1114 (7.2%). Symptoms occurred at least weekly for 773 respondents (5.0%); they occurred at least 2 times per week and were reported as moderately or severely distressing by 416 (2.7%). Of those 416 (termed RLS sufferers), 337 (81.0%) reported discussing their symptoms with a primary care physician, and only 21 (6.2%) were given a diagnosis of RLS. The SF-36 scores for RLS sufferers were significantly below population norms, matching those of patients with other chronic medical conditions. CONCLUSION: Clinically significant RLS is common (prevalence, 2.7%), is underdiagnosed, and significantly affects sleep and quality of life.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".